Agronomic and Post-Harvest Performance of Strawberry Cultivars in High Tunnel and Open-Field Environment in Southeast Virginia
Bibliographic record
Abstract
This study evaluated crop yield potential, season extension, and post-harvest parameters of strawberry cultivars grown in open-field and high tunnel, annual hill production systems. Tested cultivars included “Albion,” “Camino Real,” “Chandler,” “Merced,” “Rocco,” “Ruby June,” “San Andreas,” and “Sweet Ann.” Strawberry plugs were transplanted in the first week of October 2019. The harvest period in the high tunnel was January 2020 through June 2020, while the harvest period in the open-field was April 2020 through June 2020. Except for “Albion” (474 g/plant) having low yield, most cultivars had similar total yields in the high tunnel. “Chandler,” “Rocco” and “Sweet Ann” had the greatest total yields in the open-field (~870 to 780 g/plant). “Albion,” “Merced,” “Ruby June,” “San Andreas” and “Sweet Ann” had the greatest fruit weights in each environment. “Camino Real” and “Ruby June” had the firmest fruit in both environments. In addition, “Merced” produced firm fruits under a high tunnel environment. “Rocco,” and “Ruby June,” had the greatest total soluble solids (~8.7 °Brix) and titratable acidity (>1.85%) in the high tunnel. Total soluble solids for most cultivars were similar in open-field environments. Titratable acidity was greatest (>1.68%) for “Albion,” “Chandler,” “Rocco” and “Ruby June” in open-field production. Different cultivars offered slightly different market-desirable traits. Although the high tunnel system extended the season, achieving marketable yield in high tunnel is challenging due to various biotic and abiotic stresses. Principal component analysis indicated that a more moderate plant size may deliver a greater proportion of large, marketable berries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".